Single-cell RNA sequencing reveals that an imbalance in monocyte subsets rather than changes in gene expression patterns is a feature of postmenopausal osteoporosis.

Abstract

The role of monocytes in postmenopausal osteoporosis is widely recognized; however, the mechanisms underlying monocyte reprogramming remain unknown. In this study, single-cell RNA sequencing (scRNA-seq) was conducted on CD14+ bone marrow monocytes obtained from three postmenopausal women with normal bone mineral density (BMD) and three women with postmenopausal osteoporosis (PMOP). Monocle2 was used to classify the monocytes into 7 distinct clusters. The proportion of Cluster 1 significantly decreased in PMOP patients, while the proportion of Cluster 7 increased. Further analysis via GSEA, transcription factor activity analysis, and sc-metabolic analysis revealed significant differences between Clusters 1 and 7. Cluster 7 exhibited upregulated pathways associated with inflammation, immunity, and osteoclast differentiation, whereas Cluster 1 demonstrated the opposite results. Monocle2, TSCAN, VECTOR and scVelo data indicated that Cluster 1 represented the initial subset and that Cluster 7 represents one of the terminal subsets. BayesPrism and ssGSEA were employed to analyze the bulk transcriptome data obtained from the GEO database. The observed alterations in the proportions of Clusters 1 and 7 were validated and found to have diagnostic significance. CD16 serves as the marker gene for Cluster 7, thus leading to an increased proportion of CD16+ monocytes in women with PMOP. Flow cytometry was used to assess the consistency of outcomes with those of the bioinformatic analysis. Subsequently, an additional scRNA-seq analysis was conducted on bone marrow mononuclear cells obtained from three patients with PMOP and three postmenopausal women with normal BMD. The differential proportions of Cluster 1 and Cluster 7 were once again confirmed, with the pathological effect of Cluster 7 may attribute to cell-cell communication. The scRNA-seq findings suggest that an imbalance in monocyte subsets is a characteristic feature of PMOP. These findings elucidate the limitations of utilizing bulk transcriptome data for detecting alterations in monocytes, which may influence novel research inquiries.